More missing type annotations (#9406)

This PR fills in more missing type annotations on pydantic models. 

It's OK if it missed some annotations, we just don't want it to get
annotations wrong at this stage.

I'll do a few more passes over the same files!

libs/langchain/langchain/agents/agent_toolkits/openapi/planner.py

@@ -66,7 +66,7 @@ def _get_default_llm_chain_factory(
 class RequestsGetToolWithParsing(BaseRequestsTool, BaseTool):
     """Requests GET tool with LLM-instructed extraction of truncated responses."""
 
-    name = "requests_get"
+    name: str = "requests_get"
     """Tool name."""
     description = REQUESTS_GET_TOOL_DESCRIPTION
     """Tool description."""
@@ -96,7 +96,7 @@ class RequestsGetToolWithParsing(BaseRequestsTool, BaseTool):
 class RequestsPostToolWithParsing(BaseRequestsTool, BaseTool):
     """Requests POST tool with LLM-instructed extraction of truncated responses."""
 
-    name = "requests_post"
+    name: str = "requests_post"
     """Tool name."""
     description = REQUESTS_POST_TOOL_DESCRIPTION
     """Tool description."""
@@ -125,7 +125,7 @@ class RequestsPostToolWithParsing(BaseRequestsTool, BaseTool):
 class RequestsPatchToolWithParsing(BaseRequestsTool, BaseTool):
     """Requests PATCH tool with LLM-instructed extraction of truncated responses."""
 
-    name = "requests_patch"
+    name: str = "requests_patch"
     """Tool name."""
     description = REQUESTS_PATCH_TOOL_DESCRIPTION
     """Tool description."""
@@ -154,7 +154,7 @@ class RequestsPatchToolWithParsing(BaseRequestsTool, BaseTool):
 class RequestsDeleteToolWithParsing(BaseRequestsTool, BaseTool):
     """A tool that sends a DELETE request and parses the response."""
 
-    name = "requests_delete"
+    name: str = "requests_delete"
     """The name of the tool."""
     description = REQUESTS_DELETE_TOOL_DESCRIPTION
     """The description of the tool."""

libs/langchain/langchain/agents/openai_functions_agent/agent_token_buffer_memory.py

@@ -18,8 +18,8 @@ class AgentTokenBufferMemory(BaseChatMemory):
     """The max number of tokens to keep in the buffer. 
     Once the buffer exceeds this many tokens, the oldest messages will be pruned."""
     return_messages: bool = True
-    output_key = "output"
-    intermediate_steps_key = "intermediate_steps"
+    output_key: str = "output"
+    intermediate_steps_key: str = "intermediate_steps"
 
     @property
     def buffer(self) -> List[BaseMessage]:

libs/langchain/langchain/agents/tools.py

@@ -11,8 +11,8 @@ from langchain.tools.base import BaseTool, Tool, tool
 class InvalidTool(BaseTool):
     """Tool that is run when invalid tool name is encountered by agent."""
 
-    name = "invalid_tool"
-    description = "Called when tool name is invalid. Suggests valid tool names."
+    name: str = "invalid_tool"
+    description: str = "Called when tool name is invalid. Suggests valid tool names."
 
     def _run(
         self,

libs/langchain/langchain/callbacks/argilla_callback.py

@@ -52,11 +52,11 @@ class ArgillaCallbackHandler(BaseCallbackHandler):
         "Argilla, no doubt about it."
     """
 
-    REPO_URL = "https://github.com/argilla-io/argilla"
-    ISSUES_URL = f"{REPO_URL}/issues"
-    BLOG_URL = "https://docs.argilla.io/en/latest/guides/llms/practical_guides/use_argilla_callback_in_langchain.html"  # noqa: E501
+    REPO_URL: str = "https://github.com/argilla-io/argilla"
+    ISSUES_URL: str = f"{REPO_URL}/issues"
+    BLOG_URL: str = "https://docs.argilla.io/en/latest/guides/llms/practical_guides/use_argilla_callback_in_langchain.html"  # noqa: E501
 
-    DEFAULT_API_URL = "http://localhost:6900"
+    DEFAULT_API_URL: str = "http://localhost:6900"
 
     def __init__(
         self,

libs/langchain/langchain/callbacks/labelstudio_callback.py

@@ -97,7 +97,7 @@ class LabelStudioCallbackHandler(BaseCallbackHandler):
         >>> llm.predict('Tell me a story about a dog.')
     """
 
-    DEFAULT_PROJECT_NAME = "LangChain-%Y-%m-%d"
+    DEFAULT_PROJECT_NAME: str = "LangChain-%Y-%m-%d"
 
     def __init__(
         self,

libs/langchain/langchain/callbacks/tracers/evaluation.py

@@ -62,7 +62,7 @@ class EvaluatorCallbackHandler(BaseTracer):
         The LangSmith project name to be organize eval chain runs under.
     """
 
-    name = "evaluator_callback_handler"
+    name: str = "evaluator_callback_handler"
 
     def __init__(
         self,

libs/langchain/langchain/callbacks/tracers/run_collector.py

@@ -19,7 +19,7 @@ class RunCollectorCallbackHandler(BaseTracer):
         The ID of the example being traced. It can be either a UUID or a string.
     """
 
-    name = "run-collector_callback_handler"
+    name: str = "run-collector_callback_handler"
 
     def __init__(
         self, example_id: Optional[Union[UUID, str]] = None, **kwargs: Any

libs/langchain/langchain/callbacks/tracers/stdout.py

@@ -44,7 +44,7 @@ def elapsed(run: Any) -> str:
 class FunctionCallbackHandler(BaseTracer):
     """Tracer that calls a function with a single str parameter."""
 
-    name = "function_callback_handler"
+    name: str = "function_callback_handler"
 
     def __init__(self, function: Callable[[str], None], **kwargs: Any) -> None:
         super().__init__(**kwargs)
@@ -172,7 +172,7 @@ class FunctionCallbackHandler(BaseTracer):
 class ConsoleCallbackHandler(FunctionCallbackHandler):
     """Tracer that prints to the console."""
 
-    name = "console_callback_handler"
+    name: str = "console_callback_handler"
 
     def __init__(self, **kwargs: Any) -> None:
         super().__init__(function=print, **kwargs)

libs/langchain/langchain/chains/graph_qa/arangodb.py

@@ -29,10 +29,10 @@ class ArangoGraphQAChain(Chain):
     output_key: str = "result"  #: :meta private:
 
     # Specifies the maximum number of AQL Query Results to return
-    top_k = 10
+    top_k: int = 10
 
     # Specifies the set of AQL Query Examples that promote few-shot-learning
-    aql_examples = ""
+    aql_examples: str = ""
 
     # Specify whether to return the AQL Query in the output dictionary
     return_aql_query: bool = False
@@ -41,7 +41,7 @@ class ArangoGraphQAChain(Chain):
     return_aql_result: bool = False
 
     # Specify the maximum amount of AQL Generation attempts that should be made
-    max_aql_generation_attempts = 3
+    max_aql_generation_attempts: int = 3
 
     @property
     def input_keys(self) -> List[str]:

libs/langchain/langchain/chat_models/azureml_endpoint.py

@@ -18,7 +18,7 @@ from langchain.utils import get_from_dict_or_env
 class LlamaContentFormatter(ContentFormatterBase):
     """Content formatter for `LLaMA`."""
 
-    SUPPORTED_ROLES = ["user", "assistant", "system"]
+    SUPPORTED_ROLES: List[str] = ["user", "assistant", "system"]
 
     @staticmethod
     def _convert_message_to_dict(message: BaseMessage) -> Dict:

libs/langchain/langchain/llms/edenai.py

@@ -30,7 +30,7 @@ class EdenAI(LLM):
     for api reference check edenai documentation: http://docs.edenai.co.
     """
 
-    base_url = "https://api.edenai.run/v2"
+    base_url: str = "https://api.edenai.run/v2"
 
     edenai_api_key: Optional[str] = None
 

libs/langchain/langchain/llms/ollama.py

@@ -23,7 +23,7 @@ def _stream_response_to_generation_chunk(
 
 
 class _OllamaCommon(BaseLanguageModel):
-    base_url = "http://localhost:11434"
+    base_url: str = "http://localhost:11434"
     """Base url the model is hosted under."""
 
     model: str = "llama2"

libs/langchain/langchain/text_splitter.py

@@ -592,7 +592,7 @@ class SentenceTransformersTokenTextSplitter(TextSplitter):
     def count_tokens(self, *, text: str) -> int:
         return len(self._encode(text))
 
-    _max_length_equal_32_bit_integer = 2**32
+    _max_length_equal_32_bit_integer: int = 2**32
 
     def _encode(self, text: str) -> List[int]:
         token_ids_with_start_and_end_token_ids = self.tokenizer.encode(

libs/langchain/langchain/tools/arxiv/tool.py

@@ -11,8 +11,8 @@ from langchain.utilities.arxiv import ArxivAPIWrapper
 class ArxivQueryRun(BaseTool):
     """Tool that searches the Arxiv API."""
 
-    name = "arxiv"
-    description = (
+    name: str = "arxiv"
+    description: str = (
         "A wrapper around Arxiv.org "
         "Useful for when you need to answer questions about Physics, Mathematics, "
         "Computer Science, Quantitative Biology, Quantitative Finance, Statistics, "

libs/langchain/langchain/tools/azure_cognitive_services/form_recognizer.py

@@ -23,8 +23,8 @@ class AzureCogsFormRecognizerTool(BaseTool):
     azure_cogs_endpoint: str = ""  #: :meta private:
     doc_analysis_client: Any  #: :meta private:
 
-    name = "azure_cognitive_services_form_recognizer"
-    description = (
+    name: str = "azure_cognitive_services_form_recognizer"
+    description: str = (
         "A wrapper around Azure Cognitive Services Form Recognizer. "
         "Useful for when you need to "
         "extract text, tables, and key-value pairs from documents. "

libs/langchain/langchain/tools/azure_cognitive_services/image_analysis.py

@@ -24,8 +24,8 @@ class AzureCogsImageAnalysisTool(BaseTool):
     vision_service: Any  #: :meta private:
     analysis_options: Any  #: :meta private:
 
-    name = "azure_cognitive_services_image_analysis"
-    description = (
+    name: str = "azure_cognitive_services_image_analysis"
+    description: str = (
         "A wrapper around Azure Cognitive Services Image Analysis. "
         "Useful for when you need to analyze images. "
         "Input should be a url to an image."

libs/langchain/langchain/tools/azure_cognitive_services/speech2text.py

@@ -28,8 +28,8 @@ class AzureCogsSpeech2TextTool(BaseTool):
     speech_language: str = "en-US"  #: :meta private:
     speech_config: Any  #: :meta private:
 
-    name = "azure_cognitive_services_speech2text"
-    description = (
+    name: str = "azure_cognitive_services_speech2text"
+    description: str = (
         "A wrapper around Azure Cognitive Services Speech2Text. "
         "Useful for when you need to transcribe audio to text. "
         "Input should be a url to an audio file."

libs/langchain/langchain/tools/azure_cognitive_services/text2speech.py

@@ -24,8 +24,8 @@ class AzureCogsText2SpeechTool(BaseTool):
     speech_language: str = "en-US"  #: :meta private:
     speech_config: Any  #: :meta private:
 
-    name = "azure_cognitive_services_text2speech"
-    description = (
+    name: str = "azure_cognitive_services_text2speech"
+    description: str = (
         "A wrapper around Azure Cognitive Services Text2Speech. "
         "Useful for when you need to convert text to speech. "
     )

libs/langchain/langchain/tools/base.py

@@ -55,8 +55,8 @@ def _get_filtered_args(
 class _SchemaConfig:
     """Configuration for the pydantic model."""
 
-    extra = Extra.forbid
-    arbitrary_types_allowed = True
+    extra: Any = Extra.forbid
+    arbitrary_types_allowed: bool = True
 
 
 def create_schema_from_function(

libs/langchain/langchain/tools/bing_search/tool.py

@@ -10,8 +10,8 @@ from langchain.utilities.bing_search import BingSearchAPIWrapper
 class BingSearchRun(BaseTool):
     """Tool that queries the Bing search API."""
 
-    name = "bing_search"
-    description = (
+    name: str = "bing_search"
+    description: str = (
         "A wrapper around Bing Search. "
         "Useful for when you need to answer questions about current events. "
         "Input should be a search query."
@@ -30,8 +30,8 @@ class BingSearchRun(BaseTool):
 class BingSearchResults(BaseTool):
     """Tool that queries the Bing Search API and gets back json."""
 
-    name = "Bing Search Results JSON"
-    description = (
+    name: str = "Bing Search Results JSON"
+    description: str = (
         "A wrapper around Bing Search. "
         "Useful for when you need to answer questions about current events. "
         "Input should be a search query. Output is a JSON array of the query results"

libs/langchain/langchain/tools/brave_search/tool.py

@@ -10,8 +10,8 @@ from langchain.utilities.brave_search import BraveSearchWrapper
 class BraveSearch(BaseTool):
     """Tool that queries the BraveSearch."""
 
-    name = "brave_search"
-    description = (
+    name: str = "brave_search"
+    description: str = (
         "a search engine. "
         "useful for when you need to answer questions about current events."
         " input should be a search query."

libs/langchain/langchain/tools/dataforseo_api_search/tool.py

@@ -14,8 +14,8 @@ from langchain.utilities.dataforseo_api_search import DataForSeoAPIWrapper
 class DataForSeoAPISearchRun(BaseTool):
     """Tool that queries the DataForSeo Google search API."""
 
-    name = "dataforseo_api_search"
-    description = (
+    name: str = "dataforseo_api_search"
+    description: str = (
         "A robust Google Search API provided by DataForSeo."
         "This tool is handy when you need information about trending topics "
         "or current events."
@@ -43,8 +43,8 @@ class DataForSeoAPISearchResults(BaseTool):
     """Tool that queries the DataForSeo Google Search API
     and get back json."""
 
-    name = "DataForSeo Results JSON"
-    description = (
+    name: str = "DataForSeo Results JSON"
+    description: str = (
         "A comprehensive Google Search API provided by DataForSeo."
         "This tool is useful for obtaining real-time data on current events "
         "or popular searches."

libs/langchain/langchain/tools/ddg_search/tool.py

@@ -12,8 +12,8 @@ from langchain.utilities.duckduckgo_search import DuckDuckGoSearchAPIWrapper
 class DuckDuckGoSearchRun(BaseTool):
     """Tool that queries the DuckDuckGo search API."""
 
-    name = "duckduckgo_search"
-    description = (
+    name: str = "duckduckgo_search"
+    description: str = (
         "A wrapper around DuckDuckGo Search. "
         "Useful for when you need to answer questions about current events. "
         "Input should be a search query."
@@ -34,8 +34,8 @@ class DuckDuckGoSearchRun(BaseTool):
 class DuckDuckGoSearchResults(BaseTool):
     """Tool that queries the DuckDuckGo search API and gets back json."""
 
-    name = "DuckDuckGo Results JSON"
-    description = (
+    name: str = "DuckDuckGo Results JSON"
+    description: str = (
         "A wrapper around Duck Duck Go Search. "
         "Useful for when you need to answer questions about current events. "
         "Input should be a search query. Output is a JSON array of the query results"

libs/langchain/langchain/tools/github/tool.py

@@ -20,8 +20,8 @@ class GitHubAction(BaseTool):
 
     api_wrapper: GitHubAPIWrapper = Field(default_factory=GitHubAPIWrapper)
     mode: str
-    name = ""
-    description = ""
+    name: str = ""
+    description: str = ""
 
     def _run(
         self,

libs/langchain/langchain/tools/golden_query/tool.py

@@ -10,8 +10,8 @@ from langchain.utilities.golden_query import GoldenQueryAPIWrapper
 class GoldenQueryRun(BaseTool):
     """Tool that adds the capability to query using the Golden API and get back JSON."""
 
-    name = "Golden Query"
-    description = (
+    name: str = "Golden Query"
+    description: str = (
         "A wrapper around Golden Query API."
         " Useful for getting entities that match"
         " a natural language query from Golden's Knowledge Base."

libs/langchain/langchain/tools/google_search/tool.py

@@ -10,8 +10,8 @@ from langchain.utilities.google_search import GoogleSearchAPIWrapper
 class GoogleSearchRun(BaseTool):
     """Tool that queries the Google search API."""
 
-    name = "google_search"
-    description = (
+    name: str = "google_search"
+    description: str = (
         "A wrapper around Google Search. "
         "Useful for when you need to answer questions about current events. "
         "Input should be a search query."
@@ -30,8 +30,8 @@ class GoogleSearchRun(BaseTool):
 class GoogleSearchResults(BaseTool):
     """Tool that queries the Google Search API and gets back json."""
 
-    name = "Google Search Results JSON"
-    description = (
+    name: str = "Google Search Results JSON"
+    description: str = (
         "A wrapper around Google Search. "
         "Useful for when you need to answer questions about current events. "
         "Input should be a search query. Output is a JSON array of the query results"

libs/langchain/langchain/tools/google_serper/tool.py

@@ -14,8 +14,8 @@ from langchain.utilities.google_serper import GoogleSerperAPIWrapper
 class GoogleSerperRun(BaseTool):
     """Tool that queries the Serper.dev Google search API."""
 
-    name = "google_serper"
-    description = (
+    name: str = "google_serper"
+    description: str = (
         "A low-cost Google Search API."
         "Useful for when you need to answer questions about current events."
         "Input should be a search query."
@@ -43,8 +43,8 @@ class GoogleSerperResults(BaseTool):
     """Tool that queries the Serper.dev Google Search API
     and get back json."""
 
-    name = "google_serrper_results_json"
-    description = (
+    name: str = "google_serrper_results_json"
+    description: str = (
         "A low-cost Google Search API."
         "Useful for when you need to answer questions about current events."
         "Input should be a search query. Output is a JSON object of the query results"

libs/langchain/langchain/tools/graphql/tool.py

@@ -11,8 +11,8 @@ class BaseGraphQLTool(BaseTool):
 
     graphql_wrapper: GraphQLAPIWrapper
 
-    name = "query_graphql"
-    description = """\
+    name: str = "query_graphql"
+    description: str = """\
     Input to this tool is a detailed and correct GraphQL query, output is a result from the API.
     If the query is not correct, an error message will be returned.
     If an error is returned with 'Bad request' in it, rewrite the query and try again.

libs/langchain/langchain/tools/human/tool.py

@@ -15,8 +15,8 @@ def _print_func(text: str) -> None:
 class HumanInputRun(BaseTool):
     """Tool that asks user for input."""
 
-    name = "human"
-    description = (
+    name: str = "human"
+    description: str = (
         "You can ask a human for guidance when you think you "
         "got stuck or you are not sure what to do next. "
         "The input should be a question for the human."

libs/langchain/langchain/tools/jira/tool.py

@@ -41,8 +41,8 @@ class JiraAction(BaseTool):
 
     api_wrapper: JiraAPIWrapper = Field(default_factory=JiraAPIWrapper)
     mode: str
-    name = ""
-    description = ""
+    name: str = ""
+    description: str = ""
 
     def _run(
         self,

libs/langchain/langchain/tools/metaphor_search/tool.py

@@ -13,8 +13,8 @@ from langchain.utilities.metaphor_search import MetaphorSearchAPIWrapper
 class MetaphorSearchResults(BaseTool):
     """Tool that queries the Metaphor Search API and gets back json."""
 
-    name = "metaphor_search_results_json"
-    description = (
+    name: str = "metaphor_search_results_json"
+    description: str = (
         "A wrapper around Metaphor Search. "
         "Input should be a Metaphor-optimized query. "
         "Output is a JSON array of the query results"

libs/langchain/langchain/tools/openweathermap/tool.py

@@ -15,8 +15,8 @@ class OpenWeatherMapQueryRun(BaseTool):
         default_factory=OpenWeatherMapAPIWrapper
     )
 
-    name = "OpenWeatherMap"
-    description = (
+    name: str = "OpenWeatherMap"
+    description: str = (
         "A wrapper around OpenWeatherMap API. "
         "Useful for fetching current weather information for a specified location. "
         "Input should be a location string (e.g. London,GB)."

libs/langchain/langchain/tools/powerbi/tool.py

@@ -24,8 +24,8 @@ logger = logging.getLogger(__name__)
 class QueryPowerBITool(BaseTool):
     """Tool for querying a Power BI Dataset."""
 
-    name = "query_powerbi"
-    description = """
+    name: str = "query_powerbi"
+    description: str = """
     Input to this tool is a detailed question about the dataset, output is a result from the dataset. It will try to answer the question using the dataset, and if it cannot, it will ask for clarification.
 
     Example Input: "How many rows are in table1?"
@@ -217,8 +217,8 @@ class QueryPowerBITool(BaseTool):
 class InfoPowerBITool(BaseTool):
     """Tool for getting metadata about a PowerBI Dataset."""
 
-    name = "schema_powerbi"
-    description = """
+    name: str = "schema_powerbi"
+    description: str = """
     Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables.
     Be sure that the tables actually exist by calling list_tables_powerbi first!
 
@@ -250,8 +250,8 @@ class InfoPowerBITool(BaseTool):
 class ListPowerBITool(BaseTool):
     """Tool for getting tables names."""
 
-    name = "list_tables_powerbi"
-    description = "Input is an empty string, output is a comma separated list of tables in the database."  # noqa: E501 # pylint: disable=C0301
+    name: str = "list_tables_powerbi"
+    description: str = "Input is an empty string, output is a comma separated list of tables in the database."  # noqa: E501 # pylint: disable=C0301
     powerbi: PowerBIDataset = Field(exclude=True)
 
     class Config:

libs/langchain/langchain/tools/pubmed/tool.py

@@ -9,8 +9,8 @@ from langchain.utilities.pubmed import PubMedAPIWrapper
 class PubmedQueryRun(BaseTool):
     """Tool that searches the PubMed API."""
 
-    name = "PubMed"
-    description = (
+    name: str = "PubMed"
+    description: str = (
         "A wrapper around PubMed. "
         "Useful for when you need to answer questions about medicine, health, "
         "and biomedical topics "

libs/langchain/langchain/tools/python/tool.py

@@ -42,8 +42,8 @@ def sanitize_input(query: str) -> str:
 class PythonREPLTool(BaseTool):
     """A tool for running python code in a REPL."""
 
-    name = "Python_REPL"
-    description = (
+    name: str = "Python_REPL"
+    description: str = (
         "A Python shell. Use this to execute python commands. "
         "Input should be a valid python command. "
         "If you want to see the output of a value, you should print it out "
@@ -80,8 +80,8 @@ class PythonREPLTool(BaseTool):
 class PythonAstREPLTool(BaseTool):
     """A tool for running python code in a REPL."""
 
-    name = "python_repl_ast"
-    description = (
+    name: str = "python_repl_ast"
+    description: str = (
         "A Python shell. Use this to execute python commands. "
         "Input should be a valid python command. "
         "When using this tool, sometimes output is abbreviated - "

libs/langchain/langchain/tools/searx_search/tool.py

@@ -13,8 +13,8 @@ from langchain.utilities.searx_search import SearxSearchWrapper
 class SearxSearchRun(BaseTool):
     """Tool that queries a Searx instance."""
 
-    name = "searx_search"
-    description = (
+    name: str = "searx_search"
+    description: str = (
         "A meta search engine."
         "Useful for when you need to answer questions about current events."
         "Input should be a search query."
@@ -42,8 +42,8 @@ class SearxSearchRun(BaseTool):
 class SearxSearchResults(BaseTool):
     """Tool that queries a Searx instance and gets back json."""
 
-    name = "Searx Search Results"
-    description = (
+    name: str = "Searx Search Results"
+    description: str = (
         "A meta search engine."
         "Useful for when you need to answer questions about current events."
         "Input should be a search query. Output is a JSON array of the query results"

libs/langchain/langchain/tools/steamship_image_generation/tool.py

@@ -48,8 +48,8 @@ class SteamshipImageGenerationTool(BaseTool):
     steamship: Steamship
     return_urls: Optional[bool] = False
 
-    name = "GenerateImage"
-    description = (
+    name: str = "GenerateImage"
+    description: str = (
         "Useful for when you need to generate an image."
         "Input: A detailed text-2-image prompt describing an image"
         "Output: the UUID of a generated image"

libs/langchain/langchain/tools/wikipedia/tool.py

@@ -10,8 +10,8 @@ from langchain.utilities.wikipedia import WikipediaAPIWrapper
 class WikipediaQueryRun(BaseTool):
     """Tool that searches the Wikipedia API."""
 
-    name = "Wikipedia"
-    description = (
+    name: str = "Wikipedia"
+    description: str = (
         "A wrapper around Wikipedia. "
         "Useful for when you need to answer general questions about "
         "people, places, companies, facts, historical events, or other subjects. "

libs/langchain/langchain/tools/wolfram_alpha/tool.py

@@ -10,8 +10,8 @@ from langchain.utilities.wolfram_alpha import WolframAlphaAPIWrapper
 class WolframAlphaQueryRun(BaseTool):
     """Tool that queries using the Wolfram Alpha SDK."""
 
-    name = "wolfram_alpha"
-    description = (
+    name: str = "wolfram_alpha"
+    description: str = (
         "A wrapper around Wolfram Alpha. "
         "Useful for when you need to answer questions about Math, "
         "Science, Technology, Culture, Society and Everyday Life. "

libs/langchain/langchain/tools/youtube/search.py

@@ -18,8 +18,8 @@ from langchain.tools import BaseTool
 class YouTubeSearchTool(BaseTool):
     """Tool that queries YouTube."""
 
-    name = "youtube_search"
-    description = (
+    name: str = "youtube_search"
+    description: str = (
         "search for youtube videos associated with a person. "
         "the input to this tool should be a comma separated list, "
         "the first part contains a person name and the second a "

libs/langchain/langchain/tools/zapier/tool.py

@@ -108,8 +108,8 @@ class ZapierNLARunAction(BaseTool):
     base_prompt: str = BASE_ZAPIER_TOOL_PROMPT
     zapier_description: str
     params_schema: Dict[str, str] = Field(default_factory=dict)
-    name = ""
-    description = ""
+    name: str = ""
+    description: str = ""
 
     @root_validator
     def set_name_description(cls, values: Dict[str, Any]) -> Dict[str, Any]:
@@ -167,8 +167,8 @@ class ZapierNLAListActions(BaseTool):
 
     """
 
-    name = "ZapierNLA_list_actions"
-    description = BASE_ZAPIER_TOOL_PROMPT + (
+    name: str = "ZapierNLA_list_actions"
+    description: str = BASE_ZAPIER_TOOL_PROMPT + (
         "This tool returns a list of the user's exposed actions."
     )
     api_wrapper: ZapierNLAWrapper = Field(default_factory=ZapierNLAWrapper)

libs/langchain/tests/unit_tests/tools/test_base.py

@@ -43,9 +43,9 @@ class _MockSchema(BaseModel):
 
 
 class _MockStructuredTool(BaseTool):
-    name = "structured_api"
+    name: str = "structured_api"
     args_schema: Type[BaseModel] = _MockSchema
-    description = "A Structured Tool"
+    description: str = "A Structured Tool"
 
     def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
         return f"{arg1} {arg2} {arg3}"
@@ -69,10 +69,10 @@ def test_misannotated_base_tool_raises_error() -> None:
     with pytest.raises(SchemaAnnotationError):
 
         class _MisAnnotatedTool(BaseTool):
-            name = "structured_api"
+            name: str = "structured_api"
             # This would silently be ignored without the custom metaclass
             args_schema: BaseModel = _MockSchema  # type: ignore
-            description = "A Structured Tool"
+            description: str = "A Structured Tool"
 
             def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
                 return f"{arg1} {arg2} {arg3}"
@@ -87,9 +87,9 @@ def test_forward_ref_annotated_base_tool_accepted() -> None:
     """Test that a using forward ref annotation syntax is accepted.""" ""
 
     class _ForwardRefAnnotatedTool(BaseTool):
-        name = "structured_api"
+        name: str = "structured_api"
         args_schema: "Type[BaseModel]" = _MockSchema
-        description = "A Structured Tool"
+        description: str = "A Structured Tool"
 
         def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
             return f"{arg1} {arg2} {arg3}"
@@ -104,9 +104,9 @@ def test_subclass_annotated_base_tool_accepted() -> None:
     """Test BaseTool child w/ custom schema isn't overwritten."""
 
     class _ForwardRefAnnotatedTool(BaseTool):
-        name = "structured_api"
+        name: str = "structured_api"
         args_schema: Type[_MockSchema] = _MockSchema
-        description = "A Structured Tool"
+        description: str = "A Structured Tool"
 
         def _run(self, arg1: int, arg2: bool, arg3: Optional[dict] = None) -> str:
             return f"{arg1} {arg2} {arg3}"
@@ -154,8 +154,8 @@ def test_decorated_function_schema_equivalent() -> None:
 
 def test_args_kwargs_filtered() -> None:
     class _SingleArgToolWithKwargs(BaseTool):
-        name = "single_arg_tool"
-        description = "A  single arged tool with kwargs"
+        name: str = "single_arg_tool"
+        description: str = "A  single arged tool with kwargs"
 
         def _run(
             self,
@@ -177,8 +177,8 @@ def test_args_kwargs_filtered() -> None:
     assert tool.is_single_input
 
     class _VarArgToolWithKwargs(BaseTool):
-        name = "single_arg_tool"
-        description = "A single arged tool with kwargs"
+        name: str = "single_arg_tool"
+        description: str = "A single arged tool with kwargs"
 
         def _run(
             self,
@@ -269,8 +269,8 @@ def test_base_tool_inheritance_base_schema() -> None:
     """Test schema is correctly inferred when inheriting from BaseTool."""
 
     class _MockSimpleTool(BaseTool):
-        name = "simple_tool"
-        description = "A Simple Tool"
+        name: str = "simple_tool"
+        description: str = "A Simple Tool"
 
         def _run(self, tool_input: str) -> str:
             return f"{tool_input}"
@@ -593,8 +593,8 @@ async def test_create_async_tool() -> None:
 
 
 class _FakeExceptionTool(BaseTool):
-    name = "exception"
-    description = "an exception-throwing tool"
+    name: str = "exception"
+    description: str = "an exception-throwing tool"
     exception: Exception = ToolException()
 
     def _run(self) -> str: